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Objective. The Transit Authority Suicide Prevention (TASP) campaign was launched by the Department of Veterans Affairs (VA) in a limited number of U.S. cities to promote the use of crisis lines among veterans of military service. Methods. We obtained the daily number of calls to the VCL and National Suicide Prevention Lifeline (NSPL) for six implementation cities (where the campaign was active) and four control cities (where there was no TASP campaign messaging) for a 14-month period. To identify changes in call volume associated with campaign implementation, VCL and NSPL daily call counts for three time periods of equal length (pre-campaign, during campaign, and post-campaign) were modeled using a Poisson log-linear regression with inference based on the generalized estimating equations. Results. Statistically significant increases in calls to both the VCL and the NSPL were reported during the TASP campaign in implementation cities, but were not reported in control cities during or following the campaign. Secondary outcome measures were also reported for the VCL and included the percentage of callers who are veterans, and calls resulting in a rescue during the study period. Conclusions. Results from this study reveal some promise for suicide prevention messaging to promote the use of telephone crisis services and contribute to an emerging area of research examining the effects of campaigns on help seeking. [ABSTRACT FROM AUTHOR]

Background Post-traumatic stress disorder (PTSD) confers risk for suicidal ideation and suicide attempts but a link with suicide is not yet established. Prior analyses of users of the Veterans health administration (VHA) Health System suggest that other mental disorders strongly influence the association between PTSD and suicide in this population. We examined the association between PTSD and suicide in VHA users, with a focus on the influence of other mental disorders. Methods Data were based on linkage of VA National Patient Care Database records and the Centers for Disease Control and Prevention׳s National Death Index, with data from fiscal year 2007-2008. Analyses were based on multivariate logistic regression and structural equation models. Results Among users of VHA services studied (N=5,913,648), 0.6% (N=3620) died by suicide, including 423 who had had been diagnosed with PTSD. In unadjusted analysis, PTSD was associated with increased risk for suicide, with odds ratio, OR (95% confidence interval, 95% CI)=1.34 (1.21, 1.48). Similar results were obtained after adjustment for demographic variables and veteran characteristics. After adjustment for multiple other mental disorder diagnoses, PTSD was associated with decreased risk for suicide, OR (95% CI)=0.77 (0.69, 0.86). Major depressive disorder (MDD) had the largest influence on the association between PTSD and suicide. Limitations The analyses were cross-sectional. VHA users were studied, with unclear relevance to other populations. Conclusion The findings suggest the importance of identifying and treating comorbid MDD and other mental disorders in VHA users diagnosed with PTSD in suicide prevention efforts. [ABSTRACT FROM AUTHOR]

The World Health Organization has identified intimate partner violence (IPV) as a public health issue affecting both men and women, though significantly more information is available regarding female victimization. This study examines IPV through the lens of male victimization, focusing on a comparison of physical and mental health consequences among men who are and are not military veterans. Results from a secondary analysis of data from the Behavior Risk Factor Survey taken by 13,765 males indicated that all males, regardless of veteran status, should be screened for IPV victimization given the prevalence reported in this sample (9.5% to 12.5%). Furthermore, it was found that veteran status did affect prevalence of particular health consequences, such as depression, smoking, and binge drinking. Based on the specific comparisons examined in this study, implications for Veteran’s Administration Health Services are discussed, as is the need for more research on IPV victimization rates for men and the particular health consequences that they suffer. [ABSTRACT FROM PUBLISHER]

Purpose: The purpose of this study was to examine the effect of depression on the association between a history of military service and life satisfaction among a nationally representative sample of US men.Methods: Data from 57,905 men were obtained from the 2006 Behavioral Risk Factor Surveillance survey that assessed depression, history of military service, and life satisfaction. Multivariable logistic regression was conducted, controlling for demographics and physical health characteristics.Results: In non-depressed men, a history of military service was associated with higher odds of life satisfaction, OR (95% CI) = 1.39 (1.07, 1.81). However, the interaction between depression and a history of military service was significant, OR (95% CI) = 0.56 (0.38–0.84), such that a history of military service was associated with equivalent odds of satisfaction in depressed men, OR (95% CI) = 0.78 (0.56–1.09).Conclusions: Intervention efforts targeting depression in men with a history of military service may have a significant impact on their well-being. Future research should replicate these findings, examine potential mechanisms of the effects, and study the utility of life satisfaction measures in this population. [ABSTRACT FROM AUTHOR]

Abstract: Purpose: The current article extended previous research on the association between intimate partner violence (IPV) victimization and suicidality by longitudinally investigating their mutual impact from adolescence into early adulthood. Methods: We analyzed data from a subsample (N= 4,675) of individuals with complete data on IPV victimization from Waves II (mean age = 16.41 years), III (mean age = 22.36 years), and IV (mean age = 28.85 years) of the National Longitudinal Study of Adolescent Health. Suicidality was measured through questions assessing suicidal thoughts and suicidal attempts during the past 12 months. IPV victimization was measured through a construct assessing whether individuals had experienced threat of violence, being pushed/shoved, or had something thrown at them during the past 12 (Waves III and IV) or 18 (Wave II) months. Results: Using a path analysis framework, we found that IPV victimization and suicidality were highly stable across time. Suicidality was associated with IPV victimization prospectively, but IPV victimization did not predict suicidality prospectively. This longitudinal effect was limited to adolescent suicidality predicting IPV in early adulthood, and this effect was not qualified by gender. Conclusions: Although the findings from this study confirm the importance of considering concurrent IPV victimization in evaluating risk for suicidality, they also highlight the importance of considering a history of adolescent suicidality as an important risk marker for IPV victimization. [Copyright &y& Elsevier]

Sexual violence is a serious public health problem that has been associated with negative mental and physical health outcomes. Few existing studies have examined the prevalence and patterns of adverse mental health among victims of sexual violence using data from nationally representative samples of U.S. adults. The main objectives of this study were to identify patterns in the associations between sexual violence victimization and depression and anxiety (DA) symptoms using data from the sexual violence and DA Behavioral Risk Factor Surveillance System (BRFSS) modules. Stratified multivariate logistic regression models were conducted to test the associations between sexual violence victimization and DA controlling for demographic characteristics. Multiple stratified MANOVA models were used to detect the effect of sexual violence victimization on DA symptoms while controlling for key demographic characteristics. Among all 61,187 participants, more than 5% (n = 3,240) were victims of sexual violence, out of which 18.82% reported being diagnosed with depression, 8.37% reported an anxiety disorder, and 28.28% reported being diagnosed with DA disorder. Victims of sexual violence reported significantly higher number of days when they had trouble concentrating, sleep difficulties, poor appetite, little interest or pleasure in activities, blamed themselves for personal failure, felt depressed, and had little energy. The present study highlights the importance of collecting nationally representative data from victims of sexual violence and extends previous findings from clinically based studies. This study also serves as an example of an analytic approach that addresses a public health priority area by drawing on data from multiple topic-specific BRFSS modules. [ABSTRACT FROM PUBLISHER]

In the United States, an estimated three million men are victims of sexual violence each year, yet the majority of existing studies have evaluated the consequences and characteristics of victimization among women alone. The result has been a gap in the existing literature examining the physical and psychological consequences of sexual assault among men. The main objective of this study was to identify health outcomes, risk behaviors, and perpetrator/victim relationship characteristics among men who have experienced an attempted or completed sexual assault using data from the sexual violence module of the Behavioral Risk Factor Surveillance System survey. A total of 59,511 male respondents participated in the sexual violence module, and the majority of participants were White (73.7%), between the ages of 35 to 44 years (19.8%), married (69.0%), graduated from college (34.6%), and had an annual household income of more than US$50,000 (49.9%). Stratified multivariate logistic regression models were conducted to test the associations between victimization and health outcomes and risk behaviors controlling for age, marital status, race/ethnicity, income, education, and other potential confounders. Results of these analyses suggest important associations between health and sexual violence victimization. Specifically, men who reported unwanted attempted intercourse and attempted and completed intercourse were more likely to report poor mental health, poor life satisfaction, activity limitations, and lower emotional and social support. The current study extends knowledge of consequences of male sexual violence by considering characteristics of sexual assault and by identifying associations between victimization and a broad range of health indicators. [ABSTRACT FROM AUTHOR]

BACKGROUND: Problems related to gangs have been noted in large cities and in many schools across the United States. This study examined the patterns of alcohol, drug use, and related exposures among male and female high school students who were gang members. METHODS: Analyses were based on the Youth Violence Survey, conducted in 2004, and administered to over 80% of eligible public school students in grades 7, 9, 11, and 12 (N = 4131) in a high-risk, urban school district. The self-administered survey, completed during a class period, included measures of alcohol and drug use and related exposures. Tests of associations were determined using chi-square tests and logistic regression analyses. RESULTS: In this study, 8.8% of students reported gang membership. Students who initiated alcohol use prior to age 13 (OR = 4.90; 95% CI: 3.65–6.58), who drank alcohol 3 or more times per week (OR = 9.57; 95% CI: 6.09-15.03) and who used drugs 3 or more times per week (OR = 6.51; 95% CI: 4.59-9.25) were more likely to report gang membership than students who did not report alcohol or drug use. Boys were more likely than girls to report alcohol-related fighting and drug selling. DISCUSSION: Gang members were significantly more likely than non-gang members to have initiated alcohol early, to have reported a high prevalence of alcohol use, to have engaged in alcohol-related physical fighting, peer drinking, drug use, drug selling, peer drug selling, and having seen drug deals in their neighborhood. Schools may serve as a critically important source for intervention and prevention efforts for gang members, especially those in 7th grade, who still attend school. [ABSTRACT FROM AUTHOR]

Abstract: Early alcohol use initiation has been linked to suicide attempts among youth. However, very little is known about the potential impact of alcohol-related norms and beliefs and how these may impact the association between alcohol use and suicide attempt. This study examines the associations between early alcohol use and suicide attempts while controlling for demographic characteristics, and alcohol-related beliefs and norms (e.g., believing alcohol causes harm to health or that adults or friends disapprove of alcohol use) and potential confounders. Analyses were based on the 2006 Georgia Student Health Survey (N =175,311) of students in grades 6, 8, 10 and 12. The current analyses were limited to students in grades 8, 10 and 12, who either began drinking prior to age 13 or who were non drinkers (n =87,349). Pre-teen alcohol use initiation was associated with suicide attempts (Adj.OR=1.51; 95%CI:1.38–1.66) relative to not drinking with similar associations for boys (Adj.OR=1.72; 95%CI:1.52–1.94) and girls (Adj.OR=1.26; 95%CI:1.08–1.45). Students who believed that alcohol was harmful to their health, or that friends or adults disapproved of their alcohol use, or who had been taught about substance use in school were less likely to make a suicide attempt, although findings differed for boys and girls. Pre-teen alcohol use initiation is an important risk factor for suicide attempts among boys and girls in Georgia. Increased efforts to delay and reduce early alcohol use through clinical interventions, education, and policies that impact norms and knowledge related to alcohol use are needed and may in turn reduce suicide attempts. [Copyright &y& Elsevier]

Objective. This study examined whether youth who live in an urban, disadvantaged community are significantly more likely than youth representing the nation to engage in a range of health-compromising behaviors. Methods. Analyses were based on the Youth Violence Survey conducted in 2004 and administered to students (n=4,131) in a high-risk school district. Students in ninth grade (n=1,114) were compared with ninth-grade students in the 2003 national Youth Risk Behavior Survey (n=3,674) and the National Longitudinal Study of Adolescent Health conducted in 1995/1996 (n=3,523). Analyses assessed the differences in prevalence of risk and protective factors among ninth-grade students from the three studies using Chi-square tests. Results. The results showed that youth in this urban, disadvantaged community were significantly more likely than their peers across the country to report vandalism, theft, violence, and selling drugs. Youth in this community also reported significantly less support from their homes and schools, and less monitoring by their parents. Moreover, youth in this community were significantly less likely to binge drink or initiate alcohol use prior to age 13 than youth across the U.S. Conclusions. Youth who live in this urban, disadvantaged community reported significantly higher prevalence of some, but not all, risky behaviors than nationally representative U.S. youth. These findings highlight that some caution is justified when defining what might constitute high risk and that demographic and other characteristics need to be carefully considered when targeting certain high-risk behaviors. [ABSTRACT FROM AUTHOR]

BACKGROUND: Involvement in interpersonal violence or suicidal behaviors can have a significant impact on an adolescent’s physical health. Similarly, previous research has suggested that lived experiences, more than the presence or absence of physical ailments, can significantly influence self-assessed health status among adolescents. The purpose of this study was to examine the cross-sectional associations between involvement in violence and poor or fair self-reported health among US high school students. METHODS: Data were obtained from the 2005 national Youth Risk Behavior Survey (n = 13,953). Logistic regression analyses were conducted to determine the associations between violence-related measures and self-reported health while controlling for demographic characteristics and potential confounders. Analyses are presented for students overall and stratified by sex and race/ethnicity. RESULTS: Overall, 7.2% of students reported fair or poor self-rated health. Having been in a physical fight, having been injured in a physical fight, having attempted suicide, and having not gone to school because of safety concerns were significantly associated with fair or poor self-rated health after controlling for demographic characteristics and other potential confounders. Differences associated with race/ethnicity and sex are identified. CONCLUSIONS: Four of the 5 violence-related measures included in these analyses were significantly associated with fair or poor self-rated health. Future studies should consider the impact of involvement in violent behaviors and perceptions of both physical and mental well-being. [ABSTRACT FROM AUTHOR]

To understand the co-occurrence of multiple types of violence, the authors developed a behavioral typology based on self-reports of suicidal behaviors, physical violence, and psychological abuse. Using a sample of dating adolescents from a high-risk school district, they identified five clusters of behaviors among the 1,653 students who reported being abusive or violent in the past year. Victimization and perpetration with same-sex peers and dating partners clustered together among the students who reported the highest levels of abusive (n = 357) or violent behavior (n = 146). These students also reported high levels of suicidal behavior. There were few significant demographic differences across clusters. The implications of the results for the need to design and evaluate efforts to prevent multiple types of violence are discussed. [ABSTRACT FROM AUTHOR]

Heterogeneity of major depressive disorder (MDD) illness course complicates clinical decision-making. While efforts to use symptom profiles or biomarkers to develop clinically useful prognostic subtypes have had limited success, a recent report showed that machine learning (ML) models developed from self-reports about incident episode characteristics and comorbidities among respondents with lifetime MDD in the World Health Organization World Mental Health (WMH) Surveys predicted MDD persistence, chronicity, and severity with good accuracy. We report results of model validation in an independent prospective national household sample of 1,056 respondents with lifetime MDD at baseline. The WMH ML models were applied to these baseline data to generate predicted outcome scores that were compared to observed scores assessed 10–12 years after baseline. ML model prediction accuracy was also compared to that of conventional logistic regression models. Area under the receiver operating characteristic curve (AUC) based on ML (.63 for high chronicity and .71–.76 for the other prospective outcomes) was consistently higher than for the logistic models (.62–.70) despite the latter models including more predictors. 34.6–38.1% of respondents with subsequent high persistence-chronicity and 40.8–55.8% with the severity indicators were in the top 20% of the baseline ML predicted risk distribution, while only 0.9% of respondents with subsequent hospitalizations and 1.5% with suicide attempts were in the lowest 20% of the ML predicted risk distribution. These results confirm that clinically useful MDD risk stratification models can be generated from baseline patient self-reports and that ML methods improve on conventional methods in developing such models.

Public stigma is a significant deterrent to mental health service use for U.S. veterans. Media campaigns are often used to dispel stigmatizing beliefs and actions. Segmentation is an evidence-based practice for their effective use; however, little data has been published on veteran segments to target with anti-stigma messages. This article aims to identify and describe initial typologies of stigmatizing attitudes within a group of U.S. military veterans. Telephone-based cross-sectional surveys were conducted with a national random sample of veterans from 2014 to 2016 (N = 2142). Stigma outcomes were measured using a brief, validated instrument used in population-based surveys of public perceptions toward people with mental illness. Cluster analysis was conducted to identify specific groupings along multiple dimensions. A final four-cluster solution was identified among veterans with distinct patterns of attitudes toward mental illness and include: 1) the undecided, 2) the influencer, 3) the ambivalent, and 4) the potential ally. Several strategies were also identified for designing anti-stigma messaging toward these segments. This research demonstrates veterans can be segmented by attitudes to target with anti-stigma campaign messages. [ABSTRACT FROM AUTHOR]

Clinical trials have identified a variety of predictor variables for use in precision treatment protocols, ranging from clinical biomarkers and symptom profiles to self-report measures of various sorts. Although such variables are informative collectively, none has proven sufficiently powerful to guide optimal treatment selection individually. This has prompted growing interest in the development of composite precision treatment rules (PTRs) that are constructed by combining information across a range of predictors. But this work has been hampered by the generally small samples in randomized clinical trials and the use of suboptimal analysis methods to analyze the resulting data. In this paper, we propose to address the sample size problem by: working with large observational electronic medical record databases rather than controlled clinical trials to develop preliminary PTRs; validating these preliminary PTRs in subsequent pragmatic trials; and using ensemble machine learning methods rather than individual algorithms to carry out statistical analyses to develop the PTRs. The major challenges in this proposed approach are that treatment are not randomly assigned in observational databases and that these databases often lack measures of key prescriptive predictors and mental disorder treatment outcomes. We proposed a tiered case-cohort design approach that uses innovative methods for measuring and balancing baseline covariates and estimating PTRs to address these challenges. • Numerous methods exist to develop precision treatment rules (PTR). • Ensemble machine learning (ML) can be used to resolve uncertainty in method selection. • Using large observational databases to do this, resolves sample size problems. • Measurement of key predictors is a critical challenge in using this approach. • Innovative statistical methods exist that can address this challenge. [ABSTRACT FROM AUTHOR]

Background: Psychiatric comorbidities may complicate depression treatment by being associated with increased role impairments. However, depression symptom severity might account for these associations. Understanding the independent associations of depression severity and comorbidity with impairments could help in treatment planning. This is especially true for depressed Veterans, who have high psychiatric comorbidity rates.Methods: 2,610 Veterans beginning major depression treatment at the Veterans Health Administration (VHA) were administered a baseline self-report survey that screened for diverse psychiatric comorbidities and assessed depression severity and role impairments. Logistic and generalized linear regression models estimated univariable and multivariable associations of depression severity and comorbidities with impairments. Population attributable risk proportions (PARPs) estimated the relative importance of depression severity and comorbidities in accounting for role impairments.Results: Nearly all patients (97.8%) screened positive for at least one comorbidity and half (49.8%) for 4+ comorbidities. The most common positive screens were for generalized anxiety disorder (80.2%), posttraumatic stress disorder (77.9%), and panic/phobia (77.4%). Depression severity and comorbidities were significantly and additively associated with impairments in multivariable models. Associations were attenuated much less for depression severity than for comorbidities in multivariable versus univariable models. PARPs indicated that 15-60% of role impairments were attributable to depression severity and 5-32% to comorbidities.Limitations: The screening scales could have over-estimated comorbidity prevalence. The cross-sectional observational design cannot determine either temporal or causal priorities.Conclusions: Although positive screens for psychiatric comorbidity are pervasive among depressed VHA patients, depression severity accounts for most of the associations of these comorbidities with role impairments. [ABSTRACT FROM AUTHOR]

The authors reflect on the study by T. O. Afifi and colleagues titled "Association of child abuse exposure with suicidal ideation, suicide plans, and suicide attempts inmilitary personnel and the general population in Canada." The authors mention that the prevalence of childhood abuse is high among persons with military service history. They add that childhood abuse is related to suicidality.

Letters to the editor referring to a recent Journal article are encouraged up to 3 months after the article's appearance. By submitting a letter to the editor, the author gives permission for its publication in the Journal. Letters should not duplicate material being published or submitted elsewhere. The editors reserve the right to edit and abridge letters and to publish responses. Text is limited to 400 words and 10 references. Submit online at www.editorialmanager. com/ajph for immediate Web posting, or at ajph.edmgr.com for later print publication. Online responses are automatically considered for print publication. Queries should be addressed to the Editor-in-Chief, Mary E. Northridge, PhD, MPH, at men6@nyu.edu. [ABSTRACT FROM AUTHOR]

Insomnia and depression frequently co-occur. Significant barriers preclude a majority of patients from receiving first line treatments for both disorders in a sequential treatment episode. Although digital versions of cognitive behavioral therapy for insomnia (CBT I) and for depression (CBT D) hold some promise to meet demand, especially when paired with human support, it is unknown whether heterogeneity of treatment effects exist, such that some patients would be optimally treated with single or sequential interventions. Describe the protocol for a two-phase, prescriptive comparative effectiveness study to develop and evaluate an individualized intervention rule (IIR) for prescribing the optimal digital treament of co-occurring insomnia and depression. The proposed sample size is 2300 U.S. military veterans with insomnia and depression recruited nationally (Phase 1 = 1500; Phase 2 = 800). In each phase, the primary endpoint will be remission of both depression and insomnia 3 months following a 12-week intervention period. Phase 1 is a 5-arm randomized trial: two single digital interventions (CBT-I or CBT-D); two sequenced interventions (CBT-I + D or CBT-D + I); and a mood monitoring control condition. A cutting-edge ensemble machine learning method will be used to develop the IIR. Phase 2 will evaluate the IIR by randomizing participants with equal allocation to either the IIR predicted optimal intervention for that individual or by randomization to one the four CBT interventions. Study procedures are ongoing. Results will be reported in future manuscripts. The study will generate evidence on the optimal scalable approach to treat co-occurring insomnia and depression. [ABSTRACT FROM AUTHOR]

Background: Only a limited number of patients with major depressive disorder (MDD) respond to a first course of antidepressant medication (ADM). We investigated the feasibility of creating a baseline model to determine which of these would be among patients beginning ADM treatment in the US Veterans Health Administration (VHA). Methods: A 2018–2020 national sample of n = 660 VHA patients receiving ADM treatment for MDD completed an extensive baseline self-report assessment near the beginning of treatment and a 3-month self-report follow-up assessment. Using baseline self-report data along with administrative and geospatial data, an ensemble machine learning method was used to develop a model for 3-month treatment response defined by the Quick Inventory of Depression Symptomatology Self-Report and a modified Sheehan Disability Scale. The model was developed in a 70% training sample and tested in the remaining 30% test sample. Results: In total, 35.7% of patients responded to treatment. The prediction model had an area under the ROC curve (s.e.) of 0.66 (0.04) in the test sample. A strong gradient in probability (s.e.) of treatment response was found across three subsamples of the test sample using training sample thresholds for high [45.6% (5.5)], intermediate [34.5% (7.6)], and low [11.1% (4.9)] probabilities of response. Baseline symptom severity, comorbidity, treatment characteristics (expectations, history, and aspects of current treatment), and protective/resilience factors were the most important predictors. Conclusions: Although these results are promising, parallel models to predict response to alternative treatments based on data collected before initiating treatment would be needed for such models to help guide treatment selection. [ABSTRACT FROM AUTHOR]

Background: Fewer than half of patients with major depressive disorder (MDD) respond to psychotherapy. Pre-emptively informing patients of their likelihood of responding could be useful as part of a patient-centered treatment decision-support plan. Methods: This prospective observational study examined a national sample of 807 patients beginning psychotherapy for MDD at the Veterans Health Administration. Patients completed a self-report survey at baseline and 3-months follow-up (data collected 2018–2020). We developed a machine learning (ML) model to predict psychotherapy response at 3 months using baseline survey, administrative, and geospatial variables in a 70% training sample. Model performance was then evaluated in the 30% test sample. Results: 32.0% of patients responded to treatment after 3 months. The best ML model had an AUC (SE) of 0.652 (0.038) in the test sample. Among the one-third of patients ranked by the model as most likely to respond, 50.0% in the test sample responded to psychotherapy. In comparison, among the remaining two-thirds of patients, <25% responded to psychotherapy. The model selected 43 predictors, of which nearly all were self-report variables. Conclusions: Patients with MDD could pre-emptively be informed of their likelihood of responding to psychotherapy using a prediction tool based on self-report data. This tool could meaningfully help patients and providers in shared decision-making, although parallel information about the likelihood of responding to alternative treatments would be needed to inform decision-making across multiple treatments. [ABSTRACT FROM AUTHOR]

An estimated 60% of all Operation Enduring Freedom / Operation Iraqi Freedom (OEF/OIF) veterans who have left the military had used the US Department of Veterans Affairs (VA) for health care services as of March 31, 2015. What is not known, however, are the differences in demographic, military, and health characteristics between OEF/OIF veterans who use the VA for health care and OEF/OIF veterans who do not. We used data from the 2009-201 1 National Health Study for a New Generation of US Veterans to explore these differences. We found that VA health care users were more likely than non-VA health care users to be non-Hispanic black, to be unmarried, to have served on active duty and in the army, to have been deployed to OEF/OIF, and to have an annual income less than $35 000. The prevalence of 21 chronic medical conditions was higher among VA health care users than among non-VA health care users. OEF/OIF veterans using the VA for health care differ from nonusers with respect to demographic, military, and health characteristics. These data may be useful for developing programs and policies to address observed health disparities and achieve maximum benefit for the VA beneficiary population. [ABSTRACT FROM AUTHOR]

Background: Physician responsiveness to patient preferences for depression treatment may improve treatment adherence and clinical outcomes. Objective: To examine associations of patient treatment preferences with types of depression treatment received and treatment adherence among Veterans initiating depression treatment. Design: Patient self-report surveys at treatment initiation linked to medical records. Setting: Veterans Health Administration (VA) clinics nationally, 2018–2020. Participants: A total of 2582 patients (76.7% male, mean age 48.7 years, 62.3% Non-Hispanic White) Main Measures: Patient self-reported preferences for medication and psychotherapy on 0–10 self-anchoring visual analog scales (0="completely unwilling"; 10="completely willing"). Treatment receipt and adherence (refilling medications; attending 3+ psychotherapy sessions) over 3 months. Logistic regression models controlled for socio-demographics and geographic variables. Key Results: More patients reported strong preferences (10/10) for psychotherapy than medication (51.2% versus 36.7%, McNemar χ21=175.3, p<0.001). A total of 32.1% of patients who preferred (7–10/10) medication and 21.8% who preferred psychotherapy did not receive these treatments. Patients who strongly preferred medication were substantially more likely to receive medication than those who had strong negative preferences (odds ratios [OR]=17.5; 95% confidence interval [CI]=12.5–24.5). Compared with patients who had strong negative psychotherapy preferences, those with strong psychotherapy preferences were about twice as likely to receive psychotherapy (OR=1.9; 95% CI=1.0–3.5). Patients who strongly preferred psychotherapy were more likely to adhere to psychotherapy than those with strong negative preferences (OR=3.3; 95% CI=1.4–7.4). Treatment preferences were not associated with medication or combined treatment adherence. Patients in primary care settings had lower odds of receiving (but not adhering to) psychotherapy than patients in specialty mental health settings. Depression severity was not associated with treatment receipt or adherence. Conclusions: Mismatches between treatment preferences and treatment type received were common and associated with worse treatment adherence for psychotherapy. Future research could examine ways to decrease mismatch between patient preferences and treatments received and potential effects on patient outcomes. [ABSTRACT FROM AUTHOR]

Background: Identifying solutions to the continued rise in overdose deaths is a public health priority. However, there is evidence of change in recent substance type associated with morbidity and mortality. To better understand the continued rise in overdose deaths, in particular those attributed to opioid and stimulant use disorders, increased knowledge of patterns of use is needed.Methods: Retrospective cohort study of Veterans diagnosed with an opioid or stimulant use disorder between 2005 and 2019. The outcome of interest was diagnosis of substance use disorders, specifically examining combinations of opioid and stimulant use disorders among this population.Results: A total of 1932,188 Veterans were diagnosed with at least one substance use disorder (SUD) during the study period, 2005 through 2019. While the annual prevalence of opioid use disorder (OUD) diagnoses increased more than 155%, OUD diagnoses absent of any other SUD diagnosis increased by an average of 6.9% (95% CI, 6.4, 7.5) per year between 2005 and 2019. Between 2011 and 2019, diagnoses of co-morbid methamphetamine use disorder (MUD) and OUD increased at a higher rate than other SUD combinations.Conclusions: The prevalence of comorbid SUD, in particular co-occurring opioid and methamphetamine use disorder, increased at a higher rate than other combinations between 2005 and 2019. These findings underscore the urgent need to offer patients a combination of evidence-based treatments for each co-morbid SUD, such MOUD and contingency management for persons with comorbid opioid and methamphetamine use disorders. [ABSTRACT FROM AUTHOR]

Introduction Understanding how soldiers die after separation from military service, particularly those who die shortly after separating from service, may help to identify opportunities to ease transitions to civilian life. Materials and Methods Mortality data were analyzed for male U.S. Army soldiers who died within 18 months of their separation from service (from 1999 to 2011). Descriptive statistics were calculated for natural, accidental, suicidal, homicidal, undetermined, and legal/operation of war deaths and were stratified by age, component, time in service, and type of discharge. Crude and age-adjusted mortality rates, standardized for all years using the 2004 Regular Army population, were also calculated. The Public Health Review Board of the U.S. Army Public Health Center approved this study as Public Health Practice. Results Of the 1,884,653 male soldiers who separated from service during the study period, 3,819 died within 18 months of separation. A majority of all separations were Reserve or National Guard (58%), and 62% of decedents were in the Reserve or National Guard. Deaths from natural causes (38%) were the most common, followed by accident deaths (34%), suicides (20%), homicides (6%), undetermined deaths (2%), and legal/operation of war deaths (<1%). For overall mortality, age-adjusted rates were higher among the male U.S. population when compared to male soldiers who had separated from the Army. Conclusions The time period immediately following separation from the Army presents a unique challenge for many soldiers. Developing more effective pre-separation prevention programs that target specific risks requires knowing the causes of death for natural deaths, suicides, and accidents. Over half of all deaths occurring shortly after separation from service are preventable. Continued surveillance of specific causes of preventable deaths following separation can improve pre-separation prevention programs and transitions to post-service care. [ABSTRACT FROM AUTHOR]

Background: Health care systems struggle to identify risk factors for suicide. Adverse social determinants of health (SDH) are strong predictors of suicide risk, but most electronic health records (EHR) do not include SDH data.Objective: To determine the prevalence of SDH documentation in the EHR and how SDH are associated with suicide ideation and attempt.Design: This cross-sectional analysis included EHR data spanning October 1, 2015-September 30, 2016, from the Veterans Integrated Service Network Region 4.Participants: The study included all patients with at least one inpatient or outpatient visit (n = 293,872).Main Measurements: Adverse SDH, operationalized using Veterans Health Administration (VHA) coding for services and International Statistical Classification of Diseases and Related Health Problems (ICD)-10 codes, encompassed seven types (violence, housing instability, financial/employment problems, legal problems, familial/social problems, lack of access to care/transportation, and nonspecific psychosocial needs). We defined suicide morbidity by ICD-10 codes and data from the VHA's Suicide Prevention Applications Network. Logistic regression assessed associations of SDH with suicide morbidity, adjusting for socio-demographics and mental health diagnoses (e.g., major depression). Statistical significance was assessed with p < .01.Key Results: Overall, 16.4% of patients had at least one adverse SDH indicator. Adverse SDH exhibited dose-response-like associations with suicidal ideation and suicide attempt: each additional adverse SDH increased odds of suicidal ideation by 67% (AOR = 1.67, 99%CI = 1.60-1.75; p < .01) and suicide attempt by 49% (AOR = 1.49, 99%CI = 1.33-1.68; p < .01). Independently, each adverse SDH had strong effect sizes, ranging from 1.86 (99%CI = 1.58-2.19; p < .01) for legal issues to 3.10 (99%CI = 2.74-3.50; p < .01) for non-specific psychosocial needs in models assessing suicidal ideation and from 1.58 (99%CI = 1.10-2.27; p < .01) for employment/financial problems to 2.90 (99%CI = 2.30-4.16; p < .01) for violence in models assessing suicide attempt.Conclusions: SDH were strongly associated with suicidal ideation and suicide attempt even after adjusting for mental health diagnoses. Integration of SDH data in EHR could improve suicide prevention. [ABSTRACT FROM AUTHOR]

Objectives: In this analysis of a cohort of older homeless veterans, we examined psychosocial, health, housing, and employment characteristics to identify predictors of mortality. Method: Our sample of 3,620 older veterans entered Veteran Affairs homeless programs in years 2000-2003. Fifteen variables from a structured interview described this sample and served as predictors. National Death Index data for years 2000-2011 were used to ascertain death. Survival table analyses were conducted to estimate and plot cumulative survival functions. To determine predictors and estimate hazard functions, Cox proportional hazards regression analysis was conducted. Results: Five variables (presence of a serious health issue, hospitalization for alcohol abuse, alcohol dependency, unemployment for 3 years, and age 60+) were associated with increased risk of death; three (non-White, drug dependency, and dental problems) were associated with reduced risk. A risk score, based on total unit-weighted risk for all eight predictors, was used to identify three groups that were found to differ significantly in mortality. Conclusions: These analyses underline the jeopardy faced by older homeless veterans in terms of early death. We were able to identify several variables associated with mortality; more importantly, we were able to show that a risk score based on status for these variables was significantly related to survival. [ABSTRACT FROM AUTHOR]

Background: Early diagnosis and treatment of chronic obstructive pulmonary disease (COPD) can slow disease progression. The Department of Veterans Affairs (VA)/Department of Defense Clinical Practice Guidelines (CPG), established to improve patient outcomes, recommend the use of spirometry in the COPD diagnostic process. The aims of this study were to assess VA health care providers' performance related to CPG-recommended spirometry administration in the evaluation of newly diagnosed COPD among veterans, determine the patient characteristics that may influence the adherence rate, and compare VA concordance rates to those of other health plans.Methods: Administrative health care data related to Operations Enduring Freedom/Iraqi Freedom/New Dawn (OEF/OIF/OND) veterans was used to identify newly diagnosed COPD cases and the proportion of cases receiving spirometry. Cases were defined as veterans who had their first medical encounter with a coded diagnosis of COPD ≥ 6 months after their initial VA health care evaluation. The relationship between prediagnostic and comorbid conditions and the administration of CPG-concordant spirometry was examined using regression analyses.Findings: Among the 923,646 OEF/OIF/OND veterans receiving VA health care between January 2002 and December 2014, 32,076 (3%) had a coded diagnosis of COPD. Among those, 22,156 (69%) were identified as newly diagnosed COPD cases; only 6,827 (31%) had CPG-concordant spirometry. Concordant spirometry was more likely to occur in veterans aged ≥40. A pre-existing tobacco use disorder marginally changed the concordance rate.Discussion: VA provider adherence to CPG-concordant spirometry would decrease the prevalence of false-positive COPD cases and lead to more targeted disease treatment. Future research should focus on such cases by assessing the association between COPD diagnosis and bronchodilator responsiveness. [ABSTRACT FROM AUTHOR]

Objectives The US Veterans Health Administration (VHA) has begun using predictive modeling to identify Veterans at high suicide risk to target care. Initial analyses are reported here. Methods A penalized logistic regression model was compared with an earlier proof-of-concept logistic model. Exploratory analyses then considered commonly-used machine learning algorithms. Analyses were based on electronic medical records for all 6,360 individuals classified in the National Death Index as having died by suicide in fiscal years 2009-2011 who used VHA services the year of their death or prior year and a 1% probability sample of time-matched VHA service users alive at the index date ( n = 2,112,008). Results A penalized logistic model with 61 predictors had sensitivity comparable to the proof-of-concept model (which had 381 predictors) at target thresholds. The machine learning algorithms had relatively similar sensitivities, the highest being for Bayesian additive regression trees, with 10.7% of suicides occurred among the 1.0% of Veterans with highest predicted risk and 28.1% among the 5.0% of with highest predicted risk. Conclusions Based on these results, VHA is using penalized logistic regression in initial intervention implementation. The paper concludes with a discussion of other practical issues that might be explored to increase model performance. [ABSTRACT FROM AUTHOR]

Objectives: The US Department of Veterans Affairs' Suicide Prevention Applications Network (SPAN) is a national system for suicide event tracking and case management. The objective of this study was to assess data on suicide attempts among people using Veterans Health Administration (VHA) services. Methods: We assessed the degree of data overlap on suicide attempters reported in SPAN and the VHA's medical records from October 1, 2010, to September 30, 2014--overall, by year, and by region. Data on suicide attempters in the VHA's medical records consisted of diagnoses documented with E95 codes from the International Classification of Diseases, Ninth Revision. Results: Of 50 518 VHA patients who attempted suicide during the 4-year study period, data on fewer than half (41 %) were reported in both SPAN and the medical records; nearly 65% of patients whose suicide attempt was recorded in SPAN had no data on attempted suicide in the VHA's medical records. Conclusion: Evaluation of administrative data suggests that use of SPAN substantially increases the collection of data on suicide attempters as compared with the use of medical records alone, but neither SPAN nor the VHA's medical records identify all suicide attempters. Further research is needed to better understand the strengths and limitations of both systems and how to best combine information across systems. [ABSTRACT FROM AUTHOR]

Objective: The aim of the study was to report the mental and physical health of a population-based cohort of Gulf War and Gulf Era veterans 20 years after the war. Methods: A multimode (mail. Web, or computer-assisted telephone interviewing) heath survey of 14,252 Gulf War and Gulf Era veterans. The survey consisted of questions about general, physical, mental, reproductive, and functional health. Results: Gulf War veterans report a higher prevalence of almost all queried physical and mental health conditions. The population as a whole, however, has a significant burden of disease including high body mass index and multiple comorbid conditions. Conclusions: Gulf War veterans continue to report poorer heath than Gulf Era veterans, 20 years after the war. Chronic disease management and interventions to improve health and wellness among both Gulf War and Gulf Era veterans are necessary. [ABSTRACT FROM AUTHOR]

Abstract. Objectives: Using a sample of student service members/veterans, the current study aimed to examine the prevalence of psychiatric diagnoses and suicide-related outcomes and the association of hazardous duty with mental health. Participants: Data are from the Fall 2011 National College Health Assessment (N = 27,774). Methods: Logistic regression was used to examine (1) the association of student service member/veteran status with mental health outcomes and (2) the association of hazardous duty with mental health outcomes among student service members/veterans (n = 706). Results: Student service members/veterans had higher odds of self-harm than students without military experience. Among student service members/veterans, hazardous duty was positively associated (odds ratio [OR] = 2.00, 95% confidence interval [CI] [1.30, 3.07]) with having a psychiatric diagnosis but negatively associated (OR = 0.41, 95% CI [0.20, 0.85]) with suicidal ideation. Conclusions: Self-harm may be a unique phenomenon among service members/veterans. Suicide prevention with this population should include information about self-harm, and future research should explore whether suicidal intent underlies self-harm. [ABSTRACT FROM AUTHOR]

Abstract: Purpose: Cardiovascular disease (CVD) is the leading cause of death for women in the United States. CVD risk factors, including depression, smoking, heavy drinking, being overweight, and physical inactivity, are associated with stress and may be linked to women’s experiences of intimate partner violence (IPV) victimization. We know little about IPV and CVD risk factors among veteran women. The purpose of this study was to identify the association between lifetime IPV victimization and CVD risk factors among women, accounting for veteran status. Methods: We used data from the Centers for Disease Control and Prevention’s Behavioral Risk Factor Surveillance System for 2006 for the eight states that included the IPV module. We explored the associations between veteran status and lifetime IPV victimization and between IPV exposure and CVD risk factors, for veteran and non-veteran women. Findings: Veteran women were more likely than non-veteran women to report lifetime IPV victimization (33.0% vs. 23.8%). IPV exposure was associated with depression, smoking, and heavy drinking. We did not find evidence for an association between IPV exposure and lack of exercise or being overweight or obese, when controlling for demographic characteristics and veteran status. Conclusion: Women veterans have particularly high rates of lifetime IPV victimization. In addition, IPV victimization is associated with an increased risk of heart health risk factors. The findings suggest that we should attend to IPV exposure among veteran women and further investigate the link between IPV and military service, and the associated health impacts. [Copyright &y& Elsevier]